Abstract An important issue raised in peer‐to‐peer (P2P) applications is how to accurately and efficiently retrieve a set of K best matching data objects from different sources while minimizing the number of objects that have to be accessed. The proposed solution is to organize peers by a semantic link network representing the semantic relationships between peers' data schemas. Queries are only routed to semantically relevant peers. A pruning‐based local top‐K ranking approach is proposed to reduce the transmitted data by pruning tuples that cannot produce the desired join results with a rank value at least equal to the lowest rank value generated. Experiments evaluate its performance in terms of the number of transmitted tuples and the miss rate. Comparison with the traditional threshold algorithm for centralized systems and other top‐K ranking algorithms for P2P networks shows the features of the proposed approach. Copyright © 2006 John Wiley & Sons, Ltd.

An important issue arising from large scale data integration is how to efficiently select the top-K ranking answers from multiple sources while minimizing the transmission cost. This paper resolves this issue by proposing an efficient pruning-based approach to answer top-K join queries. The total amount of transmitted data can be greatly reduced by pruning tuples that can not produce the desired join results with a rank value greater than or equal to the rank value generated so far.

A semantic link peer‐to‐peer (P2P) network specifies and manages semantic relationships between peers' data schemas and can be used as the semantic layer of a scalable Knowledge Grid. The proposed approach consists of an automatic semantic link discovery method, a tool for building and maintaining P2P semantic link networks (P2PSLNs), a semantic‐based peer similarity measurement for efficient query routing, and the schema mapping algorithms for query reformulation and heterogeneous data integration. The proposed approach has three important aspects. First, it uses semantic links to enrich the relationships between peers' data schemas. Second, it considers not only nodes but also the XML structure in measuring the similarity between schemas to efficiently and accurately forward queries to relevant peers. Third, it copes with semantic and structural heterogeneity and data inconsistency so that peers can exchange and translate heterogeneous information within a uniform view.

The knowledge grid needs to operate with a scalable platform to provide large-scale intelligent services. A key function of such a platform is to efficiently support various complex queries in a dynamic large-scale network environment. This paper proposes a platform to support index-based path queries by incorporating a semantic overlay with an underlying structured P2P network that provides object location and management services. Various distributed indexing structures can be dynamically formed by publishing, semantic objects as indexing nodes. Queries are forwarded along the chains of semantic object pointers to search for objects. We investigate the deployment of a scalable distributed trie index for broadcast queries on key strings, propose a decentralized load balancing method for solving the problem of uneven load distribution incurred by heterogeneity of loads and node capacities and by the distributed trie index, and give an approach for improving the availability of the semantic overlay and its trie index. Experiments demonstrate the scalability of the proposed platform.

Abstract Semantic Link Network (SLN) is a semantic Web model using semantic links—the natural extension of the hyperlink‐based Web. The SLN‐Builder is a software tool that enables definition, modification and verification of, as well as access to the SLN. The SLN‐Builder can convert a SLN definition into XML descriptions for cross‐platform information exchange. The Intelligent Semantic Browser is used to visualize the SLN and carry out two types of reasoning in browsing time: small granularity reasoning by chaining semantic links and large granularity reasoning by matching semantic views of SLN. With the help of the reasoning mechanism, the browser can recommend the content that is semantically relevant to the current browsing content, and it enables users to foresee the end‐side content of a semantic link chain. This paper presents the design and implementation of the SLN‐Builder and the intelligent semantic browser as well as key algorithms. Copyright © 2004 John Wiley & Sons, Ltd.